Triple
T19660337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lubero Territory |
E472062
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Kayna
Kayna is a town located in the Lubero Territory of North Kivu Province in the eastern Democratic Republic of the Congo.
|
E1388433
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kayna | Statement: [Lubero Territory, containsSettlement, Kayna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kayna Context triple: [Lubero Territory, containsSettlement, Kayna]
-
A.
Kayna
Kayna is a small town located within the Leipzig metropolitan region in eastern Germany.
-
B.
Mayar
Mayar is a mountain in the Grampian range of Angus, Scotland, popular with hikers and often climbed together with its neighboring peak Driesh.
-
C.
Madison Davenport
Madison Davenport is an American actress and singer known for her roles in film and television, including prominent performances in horror and drama series.
-
D.
Serena
Serena was a prominent noblewoman of the late Western Roman Empire, known as the influential wife of the powerful general Stilicho and a member of the imperial Theodosian dynasty.
-
E.
Serena
Serena is one of Elle Woods’ bubbly and supportive Delta Nu sorority sisters in the Broadway musical adaptation of "Legally Blonde."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kayna Triple: [Lubero Territory, containsSettlement, Kayna]
Generated description
Kayna is a town located in the Lubero Territory of North Kivu Province in the eastern Democratic Republic of the Congo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kayna Target entity description: Kayna is a town located in the Lubero Territory of North Kivu Province in the eastern Democratic Republic of the Congo.
-
A.
Kayna
Kayna is a small town located within the Leipzig metropolitan region in eastern Germany.
-
B.
Mayar
Mayar is a mountain in the Grampian range of Angus, Scotland, popular with hikers and often climbed together with its neighboring peak Driesh.
-
C.
Madison Davenport
Madison Davenport is an American actress and singer known for her roles in film and television, including prominent performances in horror and drama series.
-
D.
Serena
Serena was a prominent noblewoman of the late Western Roman Empire, known as the influential wife of the powerful general Stilicho and a member of the imperial Theodosian dynasty.
-
E.
Serena
Serena is one of Elle Woods’ bubbly and supportive Delta Nu sorority sisters in the Broadway musical adaptation of "Legally Blonde."
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6414993ac8190b6da3702b1924b24 |
completed | April 20, 2026, 3:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a077ef5e3108190b2f7f05a01f81fc1 |
completed | May 15, 2026, 8:15 p.m. |
| NEDg | Description generation | batch_6a07801618c88190a4073957960b36c6 |
completed | May 15, 2026, 8:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0780f798888190847de6b2951d879b |
completed | May 15, 2026, 8:24 p.m. |
Created at: April 10, 2026, 1:45 p.m.